Using Multi-Attribute Decision Factors for a Modified All-or-Nothing Traffic Assignment

ISPRS International Journal of Geo-Information

EunSu Lee¹  Peter G. Oduor³  Mark Zuidgeest² 

[1] Upper Great Plains Transportation Institute, North Dakota State University, Fargo, ND 58105, USA;id="af1-ijgi-04-00883">1Upper Great Plains Transportation Institute, North Dakota State University, Fargo, ND 58105, U;Department of Geosciences, North Dakota State University, Fargo, ND 58105, USA; E-Mail:

关键词: impedance;    traffic assignment;    disruption;    multi-attribute;    route choice;   

DOI  :  10.3390/ijgi4020883

来源: mdpi

【 摘 要 】

To elucidate a realistic traffic assignment scenario, a multi-criterion decision system is essential. A traffic assignment model designed to simulate real-life situation may therefore utilize absolute and/or relative impedance. Ideally, the decision-making process should identify a set of traffic impedances (factors working against the smooth flow of traffic) along with pertinent parameters in order for the decision system to select the most optimal or the least-impeded route. In this study, we developed geospatial algorithms that consider multiple impedances. The impedances utilized in this study included, traffic patterns, capacity and congestion. The attributes of the decision-making process also prioritize multi-traffic scenarios by adopting first-in-first-out prioritization method. We also further subdivided classical impedance into either relative impedance or absolute impedance. The main advantage of this innovative multi-attribute, impedance-based trip assignment model is that it can be implemented in a manner of algebraic approach to utilize shortest path algorithm embedded in a Geographic Information Systems (GIS)—Graphical User Interface tool. Thus, the GIS package can therefore handle the multi-attribute impedance effectively. Furthermore, the method utilized in this paper displays flexibility and better adaptation to a multi-modal transportation system. Transportation, logistics, and random events, such as terrorism, can be easily analyzed with pertinent impedance.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.